title: Commentary on Steinley and Brusco (2011): recommendations and cautions.
abstract: I discuss the recommendations and cautions in Steinley and Brusco's (2011) article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the K-means procedure. As noted by researchers for over 30 years, the K-means procedure can be viewed as a special case of finite mixture modeling in which the components are in equal (fixed) proportions and are taken to be normal with a common spherical covariance matrix. In this commentary, I pay particular attention to this link and to the use of normal mixture models with arbitrary component-covariance matrices.
authors.affiliation: Department of Mathematics and Institute for Molecular Bioscience, University of Queensland, St. Lucia, Brisbane 4072, Queensland, Australia. g.mclachlan@uq.edu.au
authors.forename: Geoffrey J
authors.initials: GJ
authors.lastname: McLachlan
mesh_terms: D035841:Behavioral Research; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D005163:Factor Analysis, Statistical; D006801:Humans; D015233:Models, Statistical